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SAR image change detection method based on NSCT domain synthetic kernels

A technology of image change detection and synthesis kernel, which is applied in the field of image processing and can solve problems such as inability to detect changes in SAR images.

Inactive Publication Date: 2013-12-25
XIDIAN UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the shortcoming of above-mentioned existing problem, propose a kind of SAR image change detection method based on non-subsampled contourlet transformation NSCT domain synthesis kernel, to solve Gabor domain synthesis kernel and cannot use multi-resolution analysis to SAR Problems with image change detection

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Embodiment Construction

[0034] refer to figure 1 , the concrete implementation of the present invention comprises following training step and testing step:

[0035] 1. Training steps:

[0036] Step 1, SAR image decomposition.

[0037] Transform the original two-temporal SAR image X using the non-subsampled contourlet transform NSCT 1 ={X 1 (p,q)|1≤p≤I, 1≤q≤J} and X 2 ={X 2 (p, q)|1≤p≤I, 1≤q≤J} decomposes on S scales to obtain two-temporal images on S scales, where I and J are the length and width of the original image, ( p, q) are image pixels, S=3.

[0038] Step 2, extract image features.

[0039] For the two-temporal images on S scales obtained in step 1, extract their intensity features and texture features, and the steps are as follows:

[0040] 2.1) order Represents the low-pass subband coefficient of the two-temporal image on the mth scale, and uses the low-pass subband coefficient As the intensity feature of the two-temporal image on the mth scale, where m=1,...,S, S is the number ...

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Abstract

The invention discloses an SAR image change detection method based on NSCT domain synthetic kernels to mainly solve the problem that SAR image change detection can not be conducted through the multiresolution analysis due to existing Gabor domain synthetic kernels. The SAR image change detection method includes the steps of firstly, conducting NSCT decomposition in multiple dimensions and multiple directions on original two-time-phase SAR images; secondly, extracting the normalized strength characteristic of the decomposed two-time-phase images in each dimension and the normalized texture characteristic of the decomposed two-time-phase images in each dimension, and constructing the strength differential value synthetic kernel and the texture differential value synthetic kernel in each dimension; thirdly, enabling the differential value synthetic kernels in any dimension to be inputted into a support vector machine to be detected, and obtaining a change detection result of the dimension; fourthly, conducting determination-level inter-dimension fusion on the change detection results of all the dimensions, and obtaining a final change detection result. Compared with a method based on the existing Gabor domain synthetic kernels, the SAR image change detection method based on the NSCT domain synthetic kernels is high in detection accuracy and high in calculation efficiency and can be used for SAR image change detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to image change detection, and can be used for monitoring and evaluating ground object state changes on SAR images. Background technique [0002] SAR image change detection refers to the process of using SAR images in different periods to obtain ground object change information. It is a data analysis method established for the characteristics of SAR images to identify changes in the surface state. Although optical remote sensing has high imaging resolution, it can only be imaged during the day and is heavily affected by the weather. The SAR system has the advantages of all-weather, all-time, large coverage, etc., and has a fixed revisit cycle and high resolution. SAR images are more suitable for change detection than optical remote sensing images. With the continuous development of SAR technology, the change detection of SAR images is more and more widely used in the fields of r...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 李明吴艳贾璐王凡刘明樊建伟甘露
Owner XIDIAN UNIV
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